Effective methods of data visualization and statistical analysis

dc.contributor.author	Melsova, Alua
dc.date.accessioned	2026-05-04T11:44:41Z
dc.date.available	2026-05-04T11:44:41Z
dc.date.issued	2025
dc.identifier.isbn	978-601-08-5373-7
dc.identifier.uri	http://repository.enu.kz/handle/enu/32202
dc.description.abstract	Data visualization is an important step in the information analysis process, which allows you to quickly identify patterns, anomalies, and trends in datasets. The purpose of this work is to consider the most effective visualization methods and evaluate their applicability from the point of view of statistical analysis. The paper analyzes tools such as histograms, scatter plots, heat maps, boxplot graphs, and line graphs. Their effectiveness when working with different types of data is evaluated. Visualization software tools are also discussed, including the Python libraries Matplotlib, Seaborn, and Plotly.	ru_RU
dc.language.iso	en	ru_RU
dc.publisher	L.N. Gumilyov Eurasian National University	ru_RU
dc.title	Effective methods of data visualization and statistical analysis	ru_RU
dc.type	Article	ru_RU